Quantitative Imaging in COVID-19

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 5172

Special Issue Editor


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Guest Editor
Radiology Unit, Department of Radiology, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
Interests: computed tomography; clinical imaging; diagnostic radiology

Special Issue Information

Dear Colleagues,

At the end of 2019, a novel coronavirus named severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) was discovered in Wuhan (China) and became pandemic. SARS-CoV-2 is the cause of heterogeneous diseases, mainly respiratory, ranging from flu-like symptoms to severe interstitial pneumonia that requires hospitalization. In a small but non-negligible percentage of patients, COVID-19 pneumonia results in acute respiratory distress syndrome (ARDS) or death. Imaging is involved in COVID-19, for the diagnosis and management of patients (e.g., for discharging patients to home, for hospitalization or admission to intensive care unit). Considering that COVID-19 is a systemic disease, organs other than lung are in some cases involved (e.g., myocarditis). Quantitative imaging extracts quantifiable features from medical images for the assessment of the severity, degree of change, or status of a disease. In COVID-19, the quantification of pneumonia or the extent of well-aerated lung obtained visually or by software at admission chest CT are biomarkers of disease severity, and have prognostic significance. Nevertheless, the long-term consequences of COVID-19 pneumonia are still poorly understood. Many patients suffer from long-term sequalae, ranging from a specific syndrome with multiorgan effects or autoimmune conditions lasting weeks or months after COVID-19 illness (post-acute COVID-19 syndrome) to less-severe symptoms such as mild, unexplained dyspnea.

Therefore, the quantification of imaging biomarkers could provide additional information to better identify patients at risk of developing COVID-19 sequalae and to detect causes of unexplained symptoms after COVID-19. To contribute to the knowledge base on these issues, the following topics will be considered:

  • Evolution at imaging of COVID-19;
  • Imaging biomarkers at admission as predictors of COVID-19 long-term sequalae;
  • Quantitative imaging of long-term COVID-19 sequalae.

Dr. Davide Colombi
Guest Editor

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Keywords

  • COVID-19
  • post-acute COVID-19 syndrome
  • dyspnea
  • cough
  • respiratory failure
  • pneumonia, interstitial
  • pulmonary embolism
  • acute respiratory distress syndrome
  • myocarditis
  • neuritis
  • computer applications and software
  • pulmonary function test
  • AI (artificial intelligence)
  • thorax

Published Papers (4 papers)

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Research

16 pages, 4482 KiB  
Article
Correlation between Serum Biomarkers and Lung Ultrasound in COVID-19: An Observational Study
by Amne Mousa, Siebe G. Blok, Dian Karssen, Jurjan Aman, Jouke T. Annema, Harm Jan Bogaard, Peter I. Bonta, Mark E. Haaksma, Micah L. A. Heldeweg, Arthur W. E. Lieveld, Prabath Nanayakkara, Esther J. Nossent, Jasper M. Smit, Marry R. Smit, Alexander P. J. Vlaar, Marcus J. Schultz, Lieuwe D. J. Bos, Frederique Paulus, Pieter R. Tuinman and Amsterdam UMC COVID-19 Biobank Investigators
Diagnostics 2024, 14(4), 421; https://doi.org/10.3390/diagnostics14040421 - 14 Feb 2024
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Abstract
Serum biomarkers and lung ultrasound are important measures for prognostication and treatment allocation in patients with COVID-19. Currently, there is a paucity of studies investigating relationships between serum biomarkers and ultrasonographic biomarkers derived from lung ultrasound. This study aims to assess correlations between [...] Read more.
Serum biomarkers and lung ultrasound are important measures for prognostication and treatment allocation in patients with COVID-19. Currently, there is a paucity of studies investigating relationships between serum biomarkers and ultrasonographic biomarkers derived from lung ultrasound. This study aims to assess correlations between serum biomarkers and lung ultrasound findings. This study is a secondary analysis of four prospective observational studies in adult patients with COVID-19. Serum biomarkers included markers of epithelial injury, endothelial dysfunction and immune activation. The primary outcome was the correlation between biomarker concentrations and lung ultrasound score assessed with Pearson’s (r) or Spearman’s (rs) correlations. Forty-four patients (67 [41–88] years old, 25% female, 52% ICU patients) were included. GAS6 (rs = 0.39), CRP (rs = 0.42) and SP-D (rs = 0.36) were correlated with lung ultrasound scores. ANG-1 (rs = −0.39) was inversely correlated with lung ultrasound scores. No correlations were found between lung ultrasound score and several other serum biomarkers. In patients with COVID-19, several serum biomarkers of epithelial injury, endothelial dysfunction and immune activation correlated with lung ultrasound findings. The lack of correlations with certain biomarkers could offer opportunities for precise prognostication and targeted therapeutic interventions by integrating these unlinked biomarkers. Full article
(This article belongs to the Special Issue Quantitative Imaging in COVID-19)
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11 pages, 1251 KiB  
Article
Quantitative CT at Follow-Up of COVID-19 Pneumonia: Relationship with Pulmonary Function Tests
by Davide Colombi, Marcello Petrini, Camilla Risoli, Angelo Mangia, Gianluca Milanese, Mario Silva, Cosimo Franco, Nicola Sverzellati and Emanuele Michieletti
Diagnostics 2023, 13(21), 3328; https://doi.org/10.3390/diagnostics13213328 - 27 Oct 2023
Cited by 2 | Viewed by 757
Abstract
Background: The role of quantitative chest computed tomography (CT) is controversial in the follow-up of patients with COVID-19 pneumonia. The aim of this study was to test during the follow-up of COVID-19 pneumonia the association between pulmonary function tests (PFTs) and quantitative parameters [...] Read more.
Background: The role of quantitative chest computed tomography (CT) is controversial in the follow-up of patients with COVID-19 pneumonia. The aim of this study was to test during the follow-up of COVID-19 pneumonia the association between pulmonary function tests (PFTs) and quantitative parameters extrapolated from follow-up (FU) CT scans performed at least 6 months after COVID-19 onset. Methods: The study included patients older than 18 years old, admitted to the emergency department of our institution between 29 February 2020 and 31 December 2020, with a diagnosis of COVID-19 pneumonia, who underwent chest CT at admission and FU CT at least 6 months later; PFTs were performed within 6 months of FU CT. At FU CT, quantitative parameters of well-aerated lung and pneumonia extent were identified both visually and by software using CT density thresholds. The association between PFTs and quantitative parameters was tested by the calculation of the Spearman’s coefficient of rank correlation (rho). Results: The study included 40 patients (38% females; median age 63 years old, IQR, 56–71 years old). A significant correlation was identified between low attenuation areas% (%LAAs) <950 Hounsfield units (HU) and both forced expiratory volume in 1s/forced vital capacity (FEV1/FVC) ratio (rho −0.410, 95% CIs −0.639–−0.112, p = 0.008) and %DLCO (rho −0.426, 95% CIs −0.678–−0.084, p = 0.017). The remaining quantitative parameters failed to demonstrate a significant association with PFTs (p > 0.05). Conclusions: At follow-up, CT scans performed at least 6 months after COVID-19 pneumonia onset showed %LAAs that were inversely associated with %DLCO and could be considered a marker of irreversible lung damage. Full article
(This article belongs to the Special Issue Quantitative Imaging in COVID-19)
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16 pages, 3066 KiB  
Article
Brain Volume Changes after COVID-19 Compared to Healthy Controls by Artificial Intelligence-Based MRI Volumetry
by Zeynep Bendella, Catherine Nichols Widmann, Julian Philipp Layer, Yonah Lucas Layer, Robert Haase, Malte Sauer, Luzie Bieler, Nils Christian Lehnen, Daniel Paech, Michael T. Heneka, Alexander Radbruch and Frederic Carsten Schmeel
Diagnostics 2023, 13(10), 1716; https://doi.org/10.3390/diagnostics13101716 - 12 May 2023
Cited by 2 | Viewed by 1972
Abstract
Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is still uncertain whether there exists a potential correlation between disease severity and the effects of COVID-19 on brain integrity. Our objective was to [...] Read more.
Cohort studies that quantify volumetric brain data among individuals with different levels of COVID-19 severity are presently limited. It is still uncertain whether there exists a potential correlation between disease severity and the effects of COVID-19 on brain integrity. Our objective was to assess the potential impact of COVID-19 on measured brain volume in patients with asymptomatic/mild and severe disease after recovery from infection, compared with healthy controls, using artificial intelligence (AI)-based MRI volumetry. A total of 155 participants were prospectively enrolled in this IRB-approved analysis of three cohorts with a mild course of COVID-19 (n = 51, MILD), a severe hospitalised course (n = 48, SEV), and healthy controls (n = 56, CTL) all undergoing a standardised MRI protocol of the brain. Automated AI-based determination of various brain volumes in mL and calculation of normalised percentiles of brain volume was performed with mdbrain software, using a 3D T1-weighted magnetisation-prepared rapid gradient echo (MPRAGE) sequence. The automatically measured brain volumes and percentiles were analysed for differences between groups. The estimated influence of COVID-19 and demographic/clinical variables on brain volume was determined using multivariate analysis. There were statistically significant differences in measured brain volumes and percentiles of various brain regions among groups, even after the exclusion of patients undergoing intensive care, with significant volume reductions in COVID-19 patients, which increased with disease severity (SEV > MILD > CTL) and mainly affected the supratentorial grey matter, frontal and parietal lobes, and right thalamus. Severe COVID-19 infection, in addition to established demographic parameters such as age and sex, was a significant predictor of brain volume loss upon multivariate analysis. In conclusion, neocortical brain degeneration was detected in patients who had recovered from SARS-CoV-2 infection compared to healthy controls, worsening with greater initial COVID-19 severity and mainly affecting the fronto-parietal brain and right thalamus, regardless of ICU treatment. This suggests a direct link between COVID-19 infection and subsequent brain atrophy, which may have major implications for clinical management and future cognitive rehabilitation strategies. Full article
(This article belongs to the Special Issue Quantitative Imaging in COVID-19)
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11 pages, 2100 KiB  
Article
Quantitative Assessment of Lung Volumes and Enhancement in Patients with COVID-19: Role of Dual-Energy CT
by Giovanni Foti, Chiara Longo, Niccolò Faccioli, Massimo Guerriero, Flavio Stefanini and Dora Buonfrate
Diagnostics 2023, 13(6), 1201; https://doi.org/10.3390/diagnostics13061201 - 22 Mar 2023
Cited by 1 | Viewed by 1225
Abstract
Dual-energy computed tomography (DECT) has been used for detecting pulmonary embolism, but the role of lung perfusion DECT as a predictor of prognosis of coronavirus disease 2019 (COVID-19) has not been defined yet. The aim of our study was to explore whether the [...] Read more.
Dual-energy computed tomography (DECT) has been used for detecting pulmonary embolism, but the role of lung perfusion DECT as a predictor of prognosis of coronavirus disease 2019 (COVID-19) has not been defined yet. The aim of our study was to explore whether the enhancement pattern in COVID-19+ patients relates to the disease outcome. A secondary aim was to compare the lung volumes in two subgroups of patients. In this observational study, we considered all consecutive COVID-19+ patients who presented to the emergency room between January 2021 and December 2021 with respiratory symptoms (with mild to absent lung consolidation) and were studied by chest contrast-enhanced DECT to be eligible. Two experienced radiologists post-processed the images using the “lung-analysis” software (SyngoVia). Absolute and relative enhancement lung volumes were assessed. Patients were stratified in two subgroups depending on clinical outcome at 30 days: (i) good outcome (i.e., discharge, absence of clinical or imaging signs of disease); (ii) bad outcome (i.e., hospitalization, death). Patient sub-groups were compared using chi-square test or Fisher test for qualitative parameters, chi-square test or Spearman’s Rho test for quantitative parameters, Students’ t-test for parametric variables and Wilcoxon test for non-parametric variables. We enrolled 78 patients (45M), of whom, 16.7% had good outcomes. We did not observe any significant differences between the two groups, both in terms of the total enhancement evaluation (p = 0.679) and of the relative enhancement (p = 0.918). In contrast, the average lung volume of good outcome patients (mean value of 4262 mL) was significantly larger than that of bad outcome patients (mean value of 3577.8 mL), p = 0.0116. All COVID-19+ patients, with either good or bad outcomes, presented similar enhancement parameters and relative enhancements, underlining no differences in lung perfusion. Conversely, a significant drop in lung volume was identified in the bad outcome subgroup eligible compared to the good outcome subgroup. Full article
(This article belongs to the Special Issue Quantitative Imaging in COVID-19)
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